Publications

Eidam, EF; Bisson, K; Wang, C; Walker, C; Gibbons, A (2024). ICESat-2 and ocean particulates: A roadmap for calculating K_d from space-based lidar photon profiles. REMOTE SENSING OF ENVIRONMENT, 311, 114222.

Abstract
ICESat-2's Advanced Topographic Laser Altimeter System (ATLAS) has emerged as a useful tool for calculating attenuation signals in natural surface waters, thus improving our understanding of particulates from open-ocean plankton to nearshore suspended terrigenous sediments. While several studies have employed methods based on Beer's Law to derive attenuation coefficients (including through a machine-learning approach), a rigorous test of specific tuning parameters and processing choices has not yet been performed. Here we present comprehensive sensitivity tests of noise removal, choice of bin sizes, surface-peak exclusion, and beam pairing across four contrasting marine environments as well as solar background removal at an additional site to quantify the impacts of these processing choices on the derived photon-based attenuation coefficient K-dph. Ultimately, calculated K-dph values were not statistically sensitive to choices of horizontal bin sizes, vertical bin sizes, and surface exclusion depths with ranges of 500-2000 m, 0.25-1.0 m, and 0.5-1.0 m, respectively. Use of strong-beam data is recommended because weak-beam data introduce additional noise, though in open-ocean waters where photon counts are sparse, it may be desirable to include weak-beam data. In a daytime/nighttime data comparison, daytime data were found to be usable, though removal of the solar background increased the K-dph estimates by similar to 27-64%. A robust solution for removing afterpulses remains elusive, though a gaussian decomposition scheme was attempted. It did not, however, yield statistically different K-dph values relative to the uncorrected dataset. Detailed information about processing choices and a suggested workflow for ocean applications are provided. Together the results pave the way for expanded K-dph analyses of global datasets (including turbid coastal waters).

DOI:
10.1016/j.rse.2024.114222

ISSN:
0034-4257